Sharon AI is an Australian neocloud, delivering trusted AI infrastructure organisations need to build, train and run AI at scale. We support customers across the full AI lifecycle, from training through to inference and agentic AI, drawing on a strong ecosystem of technology and co-location partners to deliver capability where it's needed. As the first neocloud to join NVIDIA's AI Compute Program, we're growing quickly, scaling our AI Factory platform to meet rising demand for advanced compute.

The Role As Sharon AI continues to grow, we're looking for a talented Infrastructure Deployment Engineer to join our regional Delivery squad and play an important role in deploying and delivering the infrastructure layer of our AI Factories, reporting to our Regional Delivery Manager.

AI Factories are the high-performance GPU compute environments that underpin Sharon AI's AI cloud, serving customers and internal teams running large-scale training, fine-tuning and inference. In this role, the Infrastructure Deployment Engineer will take the GPU nodes and underlying cluster infrastructure of each AI Factory from hardware staging through to customer acceptance, and build and run the automation that deploys and tests them. You'll deploy, test and automate, and look for ways to make each deployment faster than the last, with reducing deployment time a core part of the job. You'll work closely with Network and Platform Deployment Engineers, on-site Data Centre Deployment Engineers, the Infrastructure and Platform teams and Operations, with exposure to cutting-edge technology at the forefront of AI infrastructure.

What You'll Be Doing

Deploying and configuring the underlying cluster infrastructure (Kubernetes and/or HPC schedulers such as Slurm)



with the Platform Deployment Engineers, from initial build through to handover

Provisioning and configuring GPU nodes: operating system images, firmware and drivers at the locked versions, to meet agreed design and performance targets

Configuring server management controllers (BMC) to the standard settings using Redfish or IPMI, and validating PCIe, NVLink and GPUDirect configuration on every node

Connecting VAST Data storage, deploying monitoring, logging and alerting agents, and applying node-level security controls and workload isolation

Working with on-site staff and the data centre provider's remote hands for any physical task, such as reseating, part swaps or console access

Running GPU node burn-in and diagnostics (DCGM), plus HPL and storage throughput tests with the platform and network engineers

Planning and executing infrastructure testing, including acceptance testing (ATP), integrated system testing (IST), and high availability, backup and recovery checks

Checking server-level (L10) test evidence from the manufacturer, recording results against pass/fail thresholds, and raising defects and hardware returns

Automating server provisioning, configuration push, OS and firmware updates, and test runs and their reports, keeping deployment code in version control with review and testing before it is used on site





Generating host configuration from the frozen design and site inventory, and keeping that inventory accurate as the source of truth

Instrumenting automation so every step is timed, giving the data to find the next delay, and feeding lessons learned back into standard playbooks and tooling

Preparing handover documentation, runbooks and as-built records, supporting Operations during the hypercare window (up to one month), and reporting progress, risks and issues to the Regional Delivery Manager

What We're Looking For

4 to 8+ years' experience in infrastructure, systems, platform or SRE engineering

Robust Linux administration and troubleshooting at scale

Experience with GPU-based systems and workloads

Strong Kubernetes and container experience, including containerised platforms in production

Experience with infrastructure-as-code (Terraform, Ansible or similar) and scripting in Python, Go or Bash

Experience building infrastructure automation, including Git, code review, CI pipelines and bare-metal or cloud provisioning through APIs

A good understanding of networking and storage

Bachelor's degree in Computer Science, Engineering or a related field, or equivalent experience

Strong communication and stakeholder management skills

Ability to manage competing priorities in a fast-paced environment

A proactive, collaborative and solutions-focused approach

Strong attention to detail

A genuine interest in AI, technology and what Sharon AI is building

Nice to have:

GPU cloud, IaaS or neocloud platform experience

Rafay, Netris or other provisioning APIs, Redfish automation, and NetBox or similar inven

📌 Infrastructure Deployment Engineer (Brisbane)
🏢 Sharon AI
📍 Brisbane